System and method for testing of automated contact center customer response systems

ABSTRACT

A system and method for testing of automated contact center customer response systems using a customer response testing system and a real time conversation engine, wherein the customer response testing system generates simulated human queries using persona profiles, sends test cases containing those queries to a contact center under test, and receives and analyzes the responses to determine whether the contact center&#39;s automated response systems understand the queries and respond appropriately.

CROSS-REFERENCE TO RELATED APPLICATIONS

Application No. Date Filed Title Current Herewith SYSTEM AND METHOD FORTESTING OF application AUTOMATED CONTACT CENTER CUSTOMER RESPONSESYSTEMS Is a continuation-in-part of: 16/392,504 Apr. 23, 2019 SYSTEMAND METHOD FOR AUTOMATED CONTACT CENTER AGENT WORKSTATION TESTING whichis a continuation of: 15/613,168 Jun. 3, 2017 SYSTEM AND METHOD FOR U.S.Pat. No. Issue Date AUTOMATED CONTACT CENTER AGENT 10,367,764 Jul. 30,2019 WORKSTATION TESTING which claims priority to, and benefit of:62/491,252 Apr. 28, 2017 SYSTEM AND METHOD FOR AUTOMATED CONTACT CENTERAGENT WORKSTATION TESTING and is also a continuation-in-part of:15/491,965 Apr. 19, 2017 SYSTEM AND METHOD FOR U.S. Pat. No. Issue DateAUTOMATED THIN CLIENT CONTACT 10,268,571 Apr. 23, 2019 CENTER AGENTDESKTOP TESTING which is a continuation-in-part of: 15/083,259 Mar. 28,2016 SYSTEM AND METHOD FOR AUTOMATED END-TO-END WEB INTERACTION TESTINGwhich is a continuation-in-part of: 14/854,023 Sep. 14, 2015 SYSTEM ANDMETHOD FOR AUTOMATED CHAT TESTING which is a continuation of: 14/141,424Dec. 27, 2013 SYSTEM AND METHOD FOR U.S. Pat. No. Issue Date AUTOMATEDCHAT TESTING 9,137,184 Sep. 15, 2015 which is a continuation of:13/936,186 Jul. 6, 2013 SYSTEM AND METHOD FOR AUTOMATED CHAT TESTINGwhich is a continuation-in-part of: 13/936,147 Jul. 6, 2013 SYSTEM ANDMETHOD FOR AUTOMATED CHAT TESTING which is a continuation-in-part of:13/567,089 Aug. 6, 2012 SYSTEM AND METHOD FOR AUTOMATED ADAPTATION ANDIMPROVEMENT OF SPEAKER AUTHENTICATION IN A VOICE BIOMETRIC SYSTEMENVIRONMENT and is also a continuation-in-part of: 12/644,343 Dec. 22,2009 INTEGRATED TESTING PLATFORM FOR U.S. Pat. No. Issue Date CONTACTCENTRES 8,625,772 Jan. 7, 2014 Current Herewith SYSTEM AND METHOD FORTESTING OF application AUTOMATED CONTACT CENTER CUSTOMER RESPONSESYSTEMS Is a continuation-in-part of: 16/392,504 Apr. 23, 2019 SYSTEMAND METHOD FOR AUTOMATED CONTACT CENTER AGENT WORKSTATION TESTING whichis a continuation of: 15/613,168 Jun. 3, 2017 SYSTEM AND METHOD FOR U.S.Pat. No. Issue Date AUTOMATED CONTACT CENTER AGENT 10,367,764 Jul. 30,2019 WORKSTATION TESTING which claims priority to, and benefit of:62/491,252 Apr. 28, 2017 SYSTEM AND METHOD FOR AUTOMATED CONTACT CENTERAGENT WORKSTATION TESTING and is also a continuation-in-part of:15/491,965 Apr. 19, 2017 SYSTEM AND METHOD FOR U.S. Pat. No. Issue DateAUTOMATED THIN CLIENT CONTACT 10,268,571 Apr. 23, 2019 CENTER AGENTDESKTOP TESTING which is a continuation-in-part of: 15/083,259 Mar. 28,2016 SYSTEM AND METHOD FOR AUTOMATED END-TO-END WEB INTERACTION TESTINGwhich is a continuation-in-part of: 14/854,023 Sep. 14, 2015 SYSTEM ANDMETHOD FOR AUTOMATED CHAT TESTING which is a continuation of: 14/141,424Dec. 27, 2013 SYSTEM AND METHOD FOR U.S. Pat. No. Issue Date AUTOMATEDCHAT TESTING 9,137,184 Sep. 15, 2015 which is a continuation-in-part of:14/140,449 Dec. 24, 2013 SYSTEM AND METHOD FOR U.S. Pat. No. Issue DateAUTOMATED CHAT TESTING 9,137,183 Sep. 15, 2015 which is a continuationof: 13/936,147 Jul. 6, 2013 SYSTEM AND METHOD FOR AUTOMATED CHAT TESTINGCurrent Herewith SYSTEM AND METHOD FOR TESTING OF application AUTOMATEDCONTACT CENTER CUSTOMER RESPONSE SYSTEMS Is a continuation-in-part of:16/392,504 Apr. 23, 2019 SYSTEM AND METHOD FOR AUTOMATED CONTACT CENTERAGENT WORKSTATION TESTING which is a continuation of: 15/613,168 Jun. 3,2017 SYSTEM AND METHOD FOR U.S. Pat. No. Issue Date AUTOMATED CONTACTCENTER AGENT 10,367,764 Jul. 30, 2019 WORKSTATION TESTING which is acontinuation-in-part of: 15/491,965 Apr. 19, 2017 SYSTEM AND METHOD FORU.S. Pat. No. Issue Date AUTOMATED THIN CLIENT CONTACT 10,268,571 Apr.23, 2019 CENTER AGENT DESKTOP TESTING and is also a continuation-in-partof: 15/157,384 May 17, 2016 SYSTEM AND METHOD FOR U.S. Pat. No. IssueDate AUTOMATED VOICE QUALITY TESTING 10,230,836 Mar. 12, 2019 which is acontinuation of: 14/709,252 May 11, 2015 SYSTEM AND METHOD FOR U.S. Pat.No. Issue Date AUTOMATED VOICE QUALITY TESTING 9,344,556 May 17, 2016which is a continuation of: 14/140,470 Dec. 25, 2013 SYSTEM AND METHODFOR U.S. Pat. No. Issue Date AUTOMATED VOICE QUALITY TESTING 9,031,221May 12, 2015 which is a continuation of: 13/936,183 Jul. 6, 2013 SYSTEMAND METHOD FOR AUTOMATED VOICE QUALITY TESTING which is acontinuation-in-part of: 13/567,089 Aug. 6, 2012 SYSTEM AND METHOD FORAUTOMATED ADAPTATION AND IMPROVEMENT OF SPEAKER AUTHENTICATION IN AVOICE BIOMETRIC SYSTEM ENVIRONMENT which is a continuation-in-part of:12/644,343 Dec. 22, 2009 INTEGRATED TESTING PLATFORM FOR U.S. Pat. No.Issue Date CONTACT CENTRES 8,625,772 Jan. 7, 2014

the entire specification of each of which is incorporated herein byreference.

BACKGROUND OF THE INVENTION Field of the Invention

The disclosure relates to the field of call center system testing, andmore particularly to the field of testing of automated customer responsesystems used by contact centers.

Discussion of the State of the Art

Contact centers are central to the function of much of today'stechnological infrastructure, allowing for customers to contact eitherlive human agents capable of answering queries regarding products andservices, or automated response systems that attempt to do the same,sometimes referring customers to human agents for more complex queries.It is the case that many contact centers have now introduced suchautomated response systems first and foremost to handle customer queriesbefore a live human agent may be reached, and in many cases performinadequately for most customers, proving difficult to understand anduse, not allowing for natural language to be used in responses to theautomated systems, taking too long or being confusing to navigate, andmore. This presents an issue for the businesses hiring these contactcenters to handle customer inquiry, as it causes frustration andalienation with their customers and prevents helpful dialogue betweencustomer and business from occurring. As well, chat and voice bots havebecome prevalent and are continuing to rise in usage. Despite theimportance of chatbots and voicebots in modern contact centers, testingof such systems for accuracy and understandability is difficult andrequires detailed manual scripting of testing routines for each desiredtest function.

Contact centers, as a result, frequently have inadequately testedsystems which not only pose frustrations for customers, but may causeissues for customer retention. What is needed is an automated way totest these systems effectively and produce reports of the results ofthese tests.

SUMMARY OF THE INVENTION

Accordingly, the inventor has conceived and reduced to practice, asystem and method for automated customer response testing that queriesautomated response systems at a client contact center, receivesresponses from the automated response systems, and analyzes theresponses to determine whether the automated response systems arefunctioning properly. The system adds complexity to its queries using a“conversation multiplier” by generating queries based on “personas” thatintroduce variations that mimic real-world customer interactions.Further, the system can evaluate text and audio communications using areal-time conversation engine by assessing the context, meaning, andlevel of formality of the communication and, where necessary, generateresponses customized to the style of the original text and audiocommunications, even additional cues such as environmental noises.

According to a preferred embodiment, a system for testing of automatedcustomer response systems at contact centers is disclosed, comprising: acustomer response testing system comprising a first plurality ofprogramming instructions stored in a memory of, and operating aprocessor of, a computing device, wherein the first plurality ofprogramming instructions, when operating on the processor, cause thecomputing device to: retrieve a test case from a test case database;retrieve a persona from a persona database; generate an ideal simulatedcustomer query based on the test case; create variations of the idealsimulated customer query using a conversation multiplier, each variationreflecting a likely real-world variant of the ideal simulated customerquery; modify each query variation based on the persona, eachmodification reflecting one or more traits of the persona; connect to acustomer response system at a contact center; transmit each modifiedquery variation of the ideal simulated customer query to a customerresponse system at a contact center; receive responses to each modifiedquery variation sent from the customer response system at the contactcenter; analyze each response received to determine whether the responseis appropriate to the modified query variation sent; and produce aresult of the analysis.

According to a preferred embodiment, a method for testing of automatedcustomer response systems at contact centers is disclosed, comprisingthe steps of: retrieving a test case from a test case database;retrieving a persona from a persona database; generating an idealsimulated customer query based on the test case as modified by thepersona; creating variations of the ideal simulated customer query usinga conversation multiplier, each variation reflecting a likely real-worldvariant of the ideal simulated customer query; modifying each queryvariation based on the persona, each modification reflecting one or moretraits of the persona; connecting to a customer response system at acontact center; transmitting each modified query variation of the idealsimulated customer query to a customer response system at a contactcenter; receiving responses to each modified query variation sent fromthe customer response system at the contact center; analyzing eachresponse received to determine whether the response is appropriate tothe modified query variation sent; and producing a result of theanalysis.

According to an aspect of an embodiment, a real time conversation enginereceives one or more of the modified query variations; analyzes the oneor more of the modified query variations to determine a context,dialect, or level of formality; receives a response corresponding toeach of the one or more of the modified query variations; analyzes eachto determine a context, dialect, or level of formality; and compares theanalysis of each of the one or more of the modified query variationswith the corresponding response for that modified query variation todetermine an appropriateness of the response.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

The accompanying drawings illustrate several embodiments of theinvention and, together with the description, serve to explain theprinciples of the invention according to the embodiments. It will beappreciated by one skilled in the art that the particular embodimentsillustrated in the drawings are merely exemplary, and are not to beconsidered as limiting of the scope of the invention or the claimsherein in any way.

FIG. 1 (PRIOR ART) is a typical system architecture diagram of a contactcenter including components commonly known in the art.

FIG. 2 is a diagram of an exemplary application of a customer responsetesting system implementation, showing the customer response testingsystem in relation to the contact center under test.

FIG. 3 is a diagram showing the overall system architecture of anexemplary customer response testing system.

FIG. 4 is a block diagram showing an aspect of the customer responsetesting system, the real time conversation engine.

FIG. 5 is a method diagram illustrating exemplary functionality of thecustomer response testing system.

FIG. 6 is a method diagram illustrating exemplary functionality of thereal time conversation engine.

FIG. 7 is a block diagram illustrating an exemplary hardwarearchitecture of a computing device used in an embodiment of theinvention.

FIG. 8 is a block diagram illustrating an exemplary logical architecturefor a client device, according to an embodiment of the invention.

FIG. 9 is a block diagram showing an exemplary architectural arrangementof clients, servers, and external services, according to an embodimentof the invention.

FIG. 10 is another block diagram illustrating an exemplary hardwarearchitecture of a computing device used in various embodiments of theinvention.

DETAILED DESCRIPTION

The inventor has conceived, and reduced to practice, a system and methodfor automated customer response testing that queries automated responsesystems at a client contact center, receives responses from theautomated response systems, and analyzes the responses to determinewhether the automated response systems are functioning properly. Thesystem adds complexity to its queries using a “conversation multiplier”by generating queries based on “personas” that introduce variations thatmimic real-world customer interactions. Further, the system can evaluatetext and audio communications using a real-time conversation engine byassessing the context, meaning, and level of formality of thecommunication and, where necessary, generate responses customized to thestyle of the original text and audio communications, even additionalcues such as environmental noises.

One or more different aspects may be described in the presentapplication. Further, for one or more of the aspects described herein,numerous alternative arrangements may be described; it should beappreciated that these are presented for illustrative purposes only andare not limiting of the aspects contained herein or the claims presentedherein in any way. One or more of the arrangements may be widelyapplicable to numerous aspects, as may be readily apparent from thedisclosure. In general, arrangements are described in sufficient detailto enable those skilled in the art to practice one or more of theaspects, and it should be appreciated that other arrangements may beutilized and that structural, logical, software, electrical and otherchanges may be made without departing from the scope of the particularaspects. Particular features of one or more of the aspects describedherein may be described with reference to one or more particular aspectsor figures that form a part of the present disclosure, and in which areshown, by way of illustration, specific arrangements of one or more ofthe aspects. It should be appreciated, however, that such features arenot limited to usage in the one or more particular aspects or figureswith reference to which they are described. The present disclosure isneither a literal description of all arrangements of one or more of theaspects nor a listing of features of one or more of the aspects thatmust be present in all arrangements.

Headings of sections provided in this patent application and the titleof this patent application are for convenience only, and are not to betaken as limiting the disclosure in any way.

Devices that are in communication with each other need not be incontinuous communication with each other, unless expressly specifiedotherwise. In addition, devices that are in communication with eachother may communicate directly or indirectly through one or morecommunication means or intermediaries, logical or physical.

A description of an aspect with several components in communication witheach other does not imply that all such components are required. To thecontrary, a variety of optional components may be described toillustrate a wide variety of possible aspects and in order to more fullyillustrate one or more aspects. Similarly, although process steps,method steps, algorithms or the like may be described in a sequentialorder, such processes, methods and algorithms may generally beconfigured to work in alternate orders, unless specifically stated tothe contrary. In other words, any sequence or order of steps that may bedescribed in this patent application does not, in and of itself,indicate a requirement that the steps be performed in that order. Thesteps of described processes may be performed in any order practical.Further, some steps may be performed simultaneously despite beingdescribed or implied as occurring non-simultaneously (e.g., because onestep is described after the other step). Moreover, the illustration of aprocess by its depiction in a drawing does not imply that theillustrated process is exclusive of other variations and modificationsthereto, does not imply that the illustrated process or any of its stepsare necessary to one or more of the aspects, and does not imply that theillustrated process is preferred. Also, steps are generally describedonce per aspect, but this does not mean they must occur once, or thatthey may only occur once each time a process, method, or algorithm iscarried out or executed. Some steps may be omitted in some aspects orsome occurrences, or some steps may be executed more than once in agiven aspect or occurrence.

When a single device or article is described herein, it will be readilyapparent that more than one device or article may be used in place of asingle device or article. Similarly, where more than one device orarticle is described herein, it will be readily apparent that a singledevice or article may be used in place of the more than one device orarticle.

The functionality or the features of a device may be alternativelyembodied by one or more other devices that are not explicitly describedas having such functionality or features. Thus, other aspects need notinclude the device itself.

Techniques and mechanisms described or referenced herein will sometimesbe described in singular form for clarity. However, it should beappreciated that particular aspects may include multiple iterations of atechnique or multiple instantiations of a mechanism unless notedotherwise. Process descriptions or blocks in figures should beunderstood as representing modules, segments, or portions of code whichinclude one or more executable instructions for implementing specificlogical functions or steps in the process. Alternate implementations areincluded within the scope of various aspects in which, for example,functions may be executed out of order from that shown or discussed,including substantially concurrently or in reverse order, depending onthe functionality involved, as would be understood by those havingordinary skill in the art.

Definitions

The term “dialect” as used herein means a regional linguistic accent,vocabulary, phraseology, style, accent, or character, whether in writingor verbal speech.

The term “environment” as used herein means the environment in which acommunication has been made, and includes, but is not limited to theaudio environment in which spoken communication occurs and the platformon which a text communication is made (e.g. written communications typedon a computer tend to have fewer mistakes and abbreviations than thosetyped on a mobile phone).

The phrase “level of formality” as used herein means the formality withwhich a communication is made. For example, communications may beformal, such as in professional writing, formal social invitations,educational writing, and the like. Communications may be informal, suchas in casual writing, and notes or letters between friends or closeacquaintances. Communications may be very informal, such as in the useof abbreviations or slang, Short Message Service (SMS) codes andsubstitutions, emojis, and the like. The level of formality may provideindirect indications about the communicator, such as level of education,closeness between communicators, emotional content, etc.

Conceptual Architecture

FIG. 1 (PRIOR ART) is a typical system architecture diagram of a contactcenter 100 known to the art. A contact center is similar to a callcenter, but a contact center has more features. While a call center maycommunicate mainly by voice, a contact center may communicate via email;text chat, such as, but not limited to, instant messaging, social mediaposts, and SMS interaction; and web interfaces in addition to voicecommunication in order to facilitate communications between a customerendpoint 110 and a resource endpoint 120. Resource 120 may include, butis not limited to, agents, sales representatives, servicerepresentatives, or collection agents handling communications withcustomers 110 on behalf of an enterprise. Resources 120 may be in-housewithin contact center 100, or may be remote, such as out-sourcing to athird party, or agents working from home. Contact center 100 may beindependently operated or networked with additional centers, and mayoften be linked to a corporate computer network.

Contact center 100 may further comprise network interface 130, textchannels 140, multimedia channels 145, and contact center components150. Text channels 140 may be communications conducted mainly throughtext, and may comprise social media 141, email 142, short messageservice (SMS) 143, or instant messaging (IM) 144, and would communicatethrough their counterparts within contact center components 150, eachrespectively being social server 159, email server 157, SMS server 160,and IM server 158.

Multimedia channels 145 may be communications conducted through avariety of mediums, and may comprise a media server 146, private branchexchange (PBX) 147, interactive voice response (IVR) 148, and bots 149.Text channels 140 and multimedia channels 145 may act as third partiesto engage with outside social media services and so a social server 159may be required to interact with the third party social media 141.Multimedia channels 145, are typically present in an enterprise'sdatacenter; but could be hosted in a remote facility, in a cloudfacility, or in a multifunction service facility.

Contact center components 150 may comprise a routing server 151, asession initiation protocol (SIP) server 152, an outbound server 153, acomputer telephony integration (CTI) server 154, a state and statistics(STAT) server 155, an automated call distribution facility (ACD) 156, anemail server 157, an IM server 158, a social server 159, a SMS server160, a routing database 170, a historical database 172, and a campaigndatabase 171. It is possible that other servers and databases may existwithin a contact center, but in this example the referenced componentsare used. Contact center components 150, including servers, databases,and other key modules that may be present in a typical contact centermay work in a black box environment, may be used collectively in onelocation, or may be spread over a plurality of locations. Contact centercomponents 150 may even be cloud-based, and more than one of eachcomponent shown may be present in a single location.

Customers 110 may communicate by use of any known form of communicationknown in the art, be it by a telephone 111, a mobile smartphone 112, atablet 113, a laptop 114, or a desktop computer 115, to name a fewexamples. Similarly, resources 120 may communicate by use of any knownform of communication known in the art, be it by a telephone 121, amobile smartphone 122, a tablet 123, a laptop 124, or a desktop computer125, to name a few examples. Communication may be conducted through anetwork interface 130 by way of at least one channel, such as a textchannel 140 or a multimedia channel 145, which communicates with aplurality of contact center components 150. Available network interfaces130 may include, but are not limited to, a public switched telephonenetwork (PSTN) 131, an internet network 132, a wide area network (WAN)133, or a local area network (LAN) 134.

To provide a few example cases, a customer calling on telephone handset111 may connect through PSTN 131 and terminate on PBX 147; a video calloriginating from tablet 123 may connect through internet connection 132and terminate on media server 146; or a customer device such as asmartphone 112 may connect via WAN 133, and terminate on IVR 148, suchas in the case of a customer calling a customer support line for a bankor a utility service. In another example, an email server 157 would beowned by the contact center 100 and would be used to communicate with athird-party email channel 142. The number of communication possibilitiesare vast between the number of possible devices of resources 120,devices of customers 110, networks 130, text channels 140, multimediachannels 145, and contact center components 150, hence the systemdiagram on FIG. 1 indicates connections between delineated groups ratherthan individual connections for clarity.

Continuing from the examples given above, in some conditions where asingle medium (such as ordinary telephone calls) is used forinteractions that require routing, media server 146 may be morespecifically PBX 147, ACD 156, or similar media-specific switchingsystem. Generally, when interactions arrive at media server 146, a routerequest, or a variation of a route request (for example, a SIP invitemessage), is sent to SIP server 152 or to an equivalent system such asCTI server 154. A route request may be a data message sent from amedia-handling device, such as media server 146, to a signaling system,such as SIP server 152. The message may comprise a request for one ormore target destinations to which to send (or route, or deliver) thespecific interaction with regard to which the route request was sent.SIP server 152 or its equivalent may, in some cases, carry out anyrequired routing logic itself, or it may forward the route requestmessage to routing server 151. Routing server 151 executes, usingstatistical data from STAT server 155 and, optionally, data from routingdatabase 170, a routing script in response to the route request messageand sends a response to media server 146 directing it to route theinteraction to a specific target in resources 120.

In another case, routing server 151 uses historical information fromhistorical database 172, or real-time information from campaign database171, or both, as well as configuration information (generally availablefrom a distributed configuration system, not shown for convenience) andinformation from routing database 170. STAT server 154 receives eventnotifications from media server 146, SIP server 152, or both regardingevents pertaining to a plurality of specific interactions handled bymedia server 146, SIP server 152, or both, and STAT server 155 computesone or more statistics for use in routing based on the received eventnotifications. Routing database 170 may comprise multiple distinctdatabases, either stored in one database management system or inseparate database management systems. Examples of data that may normallybe found in routing database 170 may include, but are not limited to:customer relationship management (CRM) data; data pertaining to one ormore social networks, including, but not limited to network graphscapturing social relationships within relevant social networks, or mediaupdates made by members of relevant social networks; skills datapertaining to a members of resources 120, which may be human agents,automated software agents, interactive voice response scripts, and soforth; data extracted from third party data sources includingcloud-based data sources such as CRM and other data fromSALESFORCE.COM™, credit data from EXPERIAN™, consumer data fromDATA.COM™; or any other data that may be useful in making routingdecisions. It will be appreciated by one having ordinary skill in theart that there are many means of data integration known in the art, anyof which may be used to obtain data from premise-based, singlemachine-based, cloud-based, public or private data sources as needed,without departing from the scope of the invention. Using informationobtained from one or more of STAT server 155, routing database 170,campaign database 172, historical database 171, and any associatedconfiguration systems, routing server 151 selects a routing target fromamong a plurality of available resource devices 120, and routing server151 then instructs SIP server 152 to route the interaction in questionto the selected resource 120, and SIP server 152 in turn directs mediaserver 146 to establish an appropriate connection between customer 110and target resource 120. In this case, the routing script comprises atleast the steps of generating a list of all possible routing targets forthe interaction regardless of the real-time state of the routing targetsusing at least an interaction identifier and a plurality of dataelements pertaining to the interaction, removing a subset of routingtargets from the generated list based on the subset of routing targetsbeing logged out to obtain a modified list, computing a plurality offitness parameters for each routing target in the modified list, sortingthe modified list based on one or more of the fitness parameters using asorting rule to obtain a sorted target list, and using a targetselection rule to consider a plurality of routing targets starting atthe beginning of the sorted target list until a routing target isselected. It should be noted that customers 110 are generally, but notnecessarily, associated with human customers or users. Nevertheless, itshould be understood that routing of other work or interaction types ispossible, although in any case, is limited to act or change withoutinput from a management team.

FIG. 2 is a diagram of an exemplary application of a customer responsetesting system implementation, showing the customer response testingsystem in relation to the contact center under test. A customer responsetesting system 210 exists which communicates over at least one, andpossibly a plurality of, networks 220, to a variety of servers used inthe contact center under test 230, 231, 232, 233, 234. Networks 220 mayinclude a Public Switched Telephone Network (PSTN), the Internet, a WideArea Network (WAN), or a Local Area Network (LAN), or any other networkcommon for telecommunications as is common in the art. In this way, acustomer response testing system 210 may be able to send and receiveemails from an email server 231, send and receive SMS messages from anSMS server 232, send and receive other text communications from a chatserver 233, and send and receive voice data from a voice server 234, orsome combination of these, such as sending an email and receiving an SMSresponse, or receiving an email as part of a voice server 234 queryresponse, such as confirming a login into a user account over the phone,or two-factor authentication systems. The customer response testingsystem 210 generates queries for each type of communication under test,initiates a communication session, makes the query, receives a responseto the query, and analyzes the response received. For instance, an emailquery may be sent from a customer response testing system 210, through anetwork or networks 220, to an email server in a contact center'sinfrastructure 231, which the contact center's automated email customerresponse system processes and formulates a reply being sent back throughthe appropriate server such as an email server 231, to be relayed backto the customer response testing system 210. Upon receipt of theautomated response from the email server, the customer response testingsystem runs a series of tests to determine the quality of the response,including such things as how quickly the response was received, whetherthe response to the query makes sense in context, whether the responseanswers the question posed by the query, etc. The analysis helps todetermine whether the automated customer response system received thequery, properly understood the query, and generated an appropriateresponse. FIG. 3 is a diagram showing the overall system architecture ofan exemplary customer response testing system. A query generator 310retrieves a test case from a test case database 305 and retrieves apersona from a persona database 315. The test case database 305 containsdata on the format and content of completed tests for the contact centerunder test, including some or a plurality of: initial query sent to thecontact center, a response from the contact center, a secondary querysent to the contact center, and a further response from the contactcenter. Such queries and responses may be of the same sort (email, SMS,etc.) or may be of different types. The persona database 315 containsdata on simulated personas to use in the generation of a contact centerquery. The persona is data representing a set of attributes for asimulated (hypothetical) customer who might interact with a contactcenter. For instance, an initial query from a test case in a test casedatabase 305 may be modified to fit the persona of a person of aparticular age, from a particular location, with certain applicableaccount or personal information which may be used in such an initialquery, the confluence of the test case and the persona being used togenerate a full query by the query generator 310. The query generatorgenerates an ideal query (i.e., a direct and clear query withouttypographical errors, grammatical mistakes, idioms, and the like, whichmay occur in real-world queries) which is sent to a conversationmultiplier 320, which produces both data for text and voice bot testing,and which multiplies a query by using alternative wording, mistakes,idiosyncrasies, neologisms, typos, and colloquialisms, or somecombination or permutation of these, with the intent of testing whetherthese variations and alterations in phrasings of a query will beaccepted by a contact center's automated response systems. Theconversation multiplier 320 may additionally use input from the personato generate queries that mimic the persona of a particular simulatedperson. For example, a particular persona may be a simulation of aperson with a specific regional dialect who often rides a bus, in whichcase the queries produced by the conversation multiplier 320 for thatpersona will modify the ideal query to use the specific regional dialectwith typographical errors introduced to simulate inaccuracies in typefrom riding on a moving bus. Further, in some embodiments, theconversation multiplier will obtain additional enhancements from areal-time conversation engine 330, whose purpose is to analyzecommunications for context, dialect, level of formality, etc., andeither introduce variations based on those analyses into queries ordetermine the appropriateness of responses to queries. Query text may besent directly from the conversation multiplier 320 to the real-timeconversation engine 330, which will send back query text enhanced withcontextual cues, regional or dialectical variants, or formality cues.After the queries are generated by the conversation multiplier, queriesintended for text-based testing (e.g. email, chat, SMS) may be sentthrough the appropriate networks 220 to the contact center under test230. For queries intended for audio-based testing (i.e., voicecommunications), the generated text queries are first fed into atext-to-speech engine 325, where the text of the query becomes convertedto audio data corresponding to speech. In some embodiments, this audiomay be sent to the real-time conversation engine 330 for enhancement(for example, to add environmental sounds such as transportation noisessimulating a particular persona riding on a bus). The text-to-speechaudio is then sent via an appropriate network 220 to the contact centerunder test 230.

Text responses from the contact center under test 230 are sent to aresponse analyzer 340, which compares the response with the originalquery to determine the quality and appropriateness of the response. Insome embodiments, responses may be sent to the real-time conversationengine for further analysis, to determine whether the context, dialect,level of formality, etc., of the response matches the context, dialect,level of formality, etc., of the query. Audio responses from the contactcenter under test 230 may first be sent to a non-speech sound filter orkeyword spotter 335 for analysis. The non-speech sound filter 335attempts to clarify the received audio by filtering out any non-word ornon-speech, or unimportant, audio data. The keyword spotter 335 attemptsto identify key words and phrases in the speech audio. Keyword spottingis faster than full speech-to-text conversion and filtering. Thisfiltered and/or searched data is then sent to a speech-to-text engine345 before being forwarded to the response analyzer 340 for analysis inthe same manner as for text-based communications. In some embodiments,the audio response may also be sent to the response analyzer 340 to usein conjunction with the real-time conversation engine to determinewhether the context, dialect, level of formality, etc., of the responsematches the context, dialect, level of formality, etc., of the query. Insome embodiments, the responses and queries will be sent to a contactcenter system mapper 341 to map the contact center's response system(e.g. on a voice call, mapping the DTMF tones associated with voiceprompts in the system).

FIG. 4 is a block diagram showing an aspect of the customer responsetesting system, the real time conversation engine 330. As text isreceived, a text analyzer 410 uses a natural language understanding(NLU) engine 411 to analyze groupings of words or sentence fragments,punctuation, and individual words in order to understand languagemeaning for a given textual input. Simultaneously, a keyword spotter(KWS) 412 may locate individual high-value words such as nouns in asentence faster than full analysis from an NLU engine 411 allowing forfaster or real-time processing of conversational data to take place. Asspeech (audio) is received, an audio analyzer 420 uses a real timespeech-to-text converter 421 to detect and convert audio speech datainto text. A real time voice quality analyzer 422 collects and analyzesperformance metrics for audio and voice quality. A real time classifier423 classifies the audio it is receiving into a plurality of audioclasses such as silence, speech, music, ring, comfort noise, earcons,etc. The real-time classifier 423 may operate in conjunction with thespeech-to-text converter 421 to send only detected speech to thespeech-to-text converter 421 to speed up operations and increaseaccuracy of conversion. Data from both the NLU engine 411 and KWS 412 issent to a conversation manager 430, which performs analyses on the textto determine the context, dialect, level of formality, etc., of thecommunication. A context analyzer 431 may use word and phraseassociations in both the query and response to determine the context inwhich the speech is taking place. A dialect analyzer 432 may usedictionaries of regional dialects and slang to determine the dialectthat the writer or speaker of a particular communication is using. Aformality analyzer 433 may use compilations of speech from persons ofdifferent educations, backgrounds, and occupations, as well ascompilations of speech from persons in different settings (e.g.,informal gatherings, office environments, weddings, etc.) as well asdictionaries of proper grammar and usage, slang, and the like, todetermine a level of formality that the writer or speaker of thecommunication is using. In some embodiments, the real time conversationengine 330 will further comprise an output generator 440, which will usethe information from the analyses from the conversation manager 430 togenerate an outgoing communication that is appropriate in terms ofcontext, dialect/slang, and level of formality to the incomingcommunication that was analyzed. For example, an incoming text query maycontain informal slang speech from a particular dialect (oftenindicating that the writer is from a particular region), which dialectanalyzer would identify as being a particular dialect and the formalityanalyzer 433 would recognize as being informal speech from that dialect.The outgoing communication would be generated by a natural languagegeneration (NLG) engine 441, matching the dialect, slang, and level offormality of the customer. In an embodiment, outgoing communication fromthe NLG would match the dialect, slang, and level of formality of the avirtual customer as defined by the persona and test case associated withthe virtual customer. Where the outgoing communication is audio, thetext may be converted to speech using a real-time text-to-speech engine442. In some embodiments, environmental cues may be introduced into theoutgoing communication by an environment simulator 443 to make thecommunication seem more natural or “real.” For example, where thecontext of the audio is an office environment, background noises from anoffice environment may be introduced into the audio, or where the writerof a text communication is riding on a bus, typographical errors may beintroduced to simulate the environment (i.e., motion) of the bus.

FIG. 5 is a method diagram illustrating exemplary functionality of thecustomer response testing system. First it retrieves a test case from atest case database 510, the test case comprising data on the entireexpected interaction between the customer response testing system andthe contact center under test. For instance, it may include data on anemail query to be sent, an email reply to be received, and a final emailresponse to be sent to the contact center. The testing system thenretrieves a persona from a persona database 520 which includes eithermanually entered or automatically generated data to simulate an actualcustomer, such as a fake name and false personal information, to testthe interaction of the contact center's communications with an actualcustomer depending on the requisite personal information required. Thetesting system then generates an ideal simulated customer query based onthe test case as modified by the persona 530, before creating variationsof the ideal simulated customer query using a conversation multiplier,each variation reflecting a likely real-world variant of the idealsimulated customer query 540, for instance using typos due to asimulated customer being on a bus during communication, or usingneologisms or colloquial speech for a geographic region or customerpersona as necessary, to test the contact center's responses to suchvariations in a customer query. After the queries are generated andmultiplied, the testing system then connects to a customer responsesystem at a contact center 550, whether through an email server, SMSserver, chat server, or voice system, and transmits each variation ofthe ideal simulated customer query to a customer response system at acontact center 560 as appropriate. It then waits to receive responses toeach variation sent from the customer response system at the contactcenter 570, on the expected channels as specified by the test case data,before analyzing each response received to determine whether theresponse is appropriate to the variation sent 580 and produce a resultof the analysis 590, indicating how long the interaction took, whetherresponses given were the expected responses, and any errors or anomaliesduring the test execution.

FIG. 6 is a method diagram illustrating exemplary functionality of thereal time conversation engine. In a first step, incoming text isreceived 601, and the text is analyzed using a natural languageunderstanding (NLU) engine to analyze groupings of words or sentencefragments, punctuation, and individual words in order to understandlanguage meaning for a given textual input 603. Simultaneously, the textis processed through a keyword spotter (KWS), which may locateindividual high-value words such as nouns in a sentence faster than fullanalysis from an NLU engine allowing for faster or real-time processingof conversational data to take place 602. In a related step, incomingspeech (audio) is received 604, and the audio is simultaneouslyprocessed to analyze performance metrics for audio and voice quality 605and to classify portions of the audio 606 into a plurality of audioclasses such as silence, speech, music, ring, comfort noise, earcons,etc. Portions of the audio that both meet a certain quality level andare classified as speech are then converted to text 607, which is thensent for further textual analysis as in steps 601, et seq. Text that hasbeen processed through an NLU engine 603 and subjected to keywordspotting 602 is then sent for contextual 608, dialectic 609, andformality analysis 610. At the context analysis stage 608, a contextanalyzer may use word and phrase associations in both the query andresponse to determine the context in which the speech is taking place.At the dialectic analysis stage 609, a dialect analyzer may usedictionaries of regional dialects and slang to determine the dialectthat the writer or speaker of a particular communication is using. Atthe formality analysis stage 610, a formality analyzer may usecompilations of speech from persons of different educations,backgrounds, and occupations, as well as compilations of speech frompersons in different settings (e.g., informal gatherings, officeenvironments, weddings, etc.) as well as dictionaries of proper grammarand usage, slang, and the like, to determine a level of formality thatthe writer or speaker of the communication is using. In someembodiments, the incoming communication (text or audio) may be passedthrough a response analyzer, which compares the response with theoriginal query to determine the quality and appropriateness of theresponse 611, although this step may also be performed outside of thereal-time conversation engine.

In some embodiments, the real time conversation engine will use theinformation from the contextual, dialectic, and formality analyses togenerate an outgoing communication that is appropriate in terms ofcontext, dialect/slang, and level of formality to the incomingcommunication that was analyzed 612. For example, an incoming text querymay contain informal slang speech from a particular dialect (oftenindicating that the writer is from a particular region), which dialecticanalysis would identify as being a particular dialect and the formalityanalysis would recognize as being informal speech from that dialect. Theoutgoing communication would be generated by a natural languagegeneration (NLG) engine using the same dialect and a similar level ofinformality. Where the outgoing communication is audio, the text may beconverted to speech using a real-time text-to-speech engine (not shown).In some embodiments, environmental cues may be introduced into theoutgoing communication by an environment simulator to make thecommunication seem more “real” or natural 613. For example, where thecontext of the audio is an office environment, background noises from anoffice environment may be introduced into the audio, or where the writerof a text communication is riding on a bus, typographical errors may beintroduced to simulate the environment (i.e., motion) of the bus.

Hardware Architecture

Generally, the techniques disclosed herein may be implemented onhardware or a combination of software and hardware. For example, theymay be implemented in an operating system kernel, in a separate userprocess, in a library package bound into network applications, on aspecially constructed machine, on an application-specific integratedcircuit (ASIC), or on a network interface card.

Software/hardware hybrid implementations of at least some of the aspectsdisclosed herein may be implemented on a programmable network-residentmachine (which should be understood to include intermittently connectednetwork-aware machines) selectively activated or reconfigured by acomputer program stored in memory. Such network devices may havemultiple network interfaces that may be configured or designed toutilize different types of network communication protocols. A generalarchitecture for some of these machines may be described herein in orderto illustrate one or more exemplary means by which a given unit offunctionality may be implemented. According to specific aspects, atleast some of the features or functionalities of the various aspectsdisclosed herein may be implemented on one or more general-purposecomputers associated with one or more networks, such as for example anend-user computer system, a client computer, a network server or otherserver system, a mobile computing device (e.g., tablet computing device,mobile phone, smartphone, laptop, or other appropriate computingdevice), a consumer electronic device, a music player, or any othersuitable electronic device, router, switch, or other suitable device, orany combination thereof. In at least some aspects, at least some of thefeatures or functionalities of the various aspects disclosed herein maybe implemented in one or more virtualized computing environments (e.g.,network computing clouds, virtual machines hosted on one or morephysical computing machines, or other appropriate virtual environments).

Referring now to FIG. 7, there is shown a block diagram depicting anexemplary computing device 10 suitable for implementing at least aportion of the features or functionalities disclosed herein. Computingdevice 10 may be, for example, any one of the computing machines listedin the previous paragraph, or indeed any other electronic device capableof executing software- or hardware-based instructions according to oneor more programs stored in memory. Computing device 10 may be configuredto communicate with a plurality of other computing devices, such asclients or servers, over communications networks such as a wide areanetwork, a metropolitan area network, a local area network, a wirelessnetwork, the Internet, or any other network, using known protocols forsuch communication, whether wireless or wired.

In one aspect, computing device 10 includes one or more centralprocessing units (CPU) 12, one or more interfaces 15, and one or morebusses 14 (such as a peripheral component interconnect (PCI) bus). Whenacting under the control of appropriate software or firmware, CPU 12 maybe responsible for implementing specific functions associated with thefunctions of a specifically configured computing device or machine. Forexample, in at least one aspect, a computing device 10 may be configuredor designed to function as a server system utilizing CPU 12, localmemory 11 and/or remote memory 16, and interface(s) 15. In at least oneaspect, CPU 12 may be caused to perform one or more of the differenttypes of functions and/or operations under the control of softwaremodules or components, which for example, may include an operatingsystem and any appropriate applications software, drivers, and the like.

CPU 12 may include one or more processors 13 such as, for example, aprocessor from one of the Intel, ARM, Qualcomm, and AMD families ofmicroprocessors. In some aspects, processors 13 may include speciallydesigned hardware such as application-specific integrated circuits(ASICs), electrically erasable programmable read-only memories(EEPROMs), field-programmable gate arrays (FPGAs), and so forth, forcontrolling operations of computing device 10. In a particular aspect, alocal memory 11 (such as non-volatile random access memory (RAM) and/orread-only memory (ROM), including for example one or more levels ofcached memory) may also form part of CPU 12. However, there are manydifferent ways in which memory may be coupled to system 10. Memory 11may be used for a variety of purposes such as, for example, cachingand/or storing data, programming instructions, and the like. It shouldbe further appreciated that CPU 12 may be one of a variety ofsystem-on-a-chip (SOC) type hardware that may include additionalhardware such as memory or graphics processing chips, such as a QUALCOMMSNAPDRAGON™ or SAMSUNG EXYNOS™ CPU as are becoming increasingly commonin the art, such as for use in mobile devices or integrated devices.

As used herein, the term “processor” is not limited merely to thoseintegrated circuits referred to in the art as a processor, a mobileprocessor, or a microprocessor, but broadly refers to a microcontroller,a microcomputer, a programmable logic controller, anapplication-specific integrated circuit, and any other programmablecircuit.

In one aspect, interfaces 15 are provided as network interface cards(NICs). Generally, NICs control the sending and receiving of datapackets over a computer network; other types of interfaces 15 may forexample support other peripherals used with computing device 10. Amongthe interfaces that may be provided are Ethernet interfaces, frame relayinterfaces, cable interfaces, DSL interfaces, token ring interfaces,graphics interfaces, and the like. In addition, various types ofinterfaces may be provided such as, for example, universal serial bus(USB), Serial, Ethernet, FIREWIRE™, THUNDERBOLT™, PCI, parallel, radiofrequency (RF), BLUETOOTH™, near-field communications (e.g., usingnear-field magnetics), 802.11 (WiFi), frame relay, TCP/IP, ISDN, fastEthernet interfaces, Gigabit Ethernet interfaces, Serial ATA (SATA) orexternal SATA (eSATA) interfaces, high-definition multimedia interface(HDMI), digital visual interface (DVI), analog or digital audiointerfaces, asynchronous transfer mode (ATM) interfaces, high-speedserial interface (HSSI) interfaces, Point of Sale (POS) interfaces,fiber data distributed interfaces (FDDIs), and the like. Generally, suchinterfaces 15 may include physical ports appropriate for communicationwith appropriate media. In some cases, they may also include anindependent processor (such as a dedicated audio or video processor, asis common in the art for high-fidelity AN hardware interfaces) and, insome instances, volatile and/or non-volatile memory (e.g., RAM).

Although the system shown in FIG. 7 illustrates one specificarchitecture for a computing device 10 for implementing one or more ofthe aspects described herein, it is by no means the only devicearchitecture on which at least a portion of the features and techniquesdescribed herein may be implemented. For example, architectures havingone or any number of processors 13 may be used, and such processors 13may be present in a single device or distributed among any number ofdevices. In one aspect, a single processor 13 handles communications aswell as routing computations, while in other aspects a separatededicated communications processor may be provided. In various aspects,different types of features or functionalities may be implemented in asystem according to the aspect that includes a client device (such as atablet device or smartphone running client software) and server systems(such as a server system described in more detail below).

Regardless of network device configuration, the system of an aspect mayemploy one or more memories or memory modules (such as, for example,remote memory block 16 and local memory 11) configured to store data,program instructions for the general-purpose network operations, orother information relating to the functionality of the aspects describedherein (or any combinations of the above). Program instructions maycontrol execution of or comprise an operating system and/or one or moreapplications, for example. Memory 16 or memories 11, 16 may also beconfigured to store data structures, configuration data, encryptiondata, historical system operations information, or any other specific orgeneric non-program information described herein.

Because such information and program instructions may be employed toimplement one or more systems or methods described herein, at least somenetwork device aspects may include nontransitory machine-readablestorage media, which, for example, may be configured or designed tostore program instructions, state information, and the like forperforming various operations described herein. Examples of suchnontransitory machine-readable storage media include, but are notlimited to, magnetic media such as hard disks, floppy disks, andmagnetic tape; optical media such as CD-ROM disks; magneto-optical mediasuch as optical disks, and hardware devices that are speciallyconfigured to store and perform program instructions, such as read-onlymemory devices (ROM), flash memory (as is common in mobile devices andintegrated systems), solid state drives (SSD) and “hybrid SSD” storagedrives that may combine physical components of solid state and hard diskdrives in a single hardware device (as are becoming increasingly commonin the art with regard to personal computers), memristor memory, randomaccess memory (RAM), and the like. It should be appreciated that suchstorage means may be integral and non-removable (such as RAM hardwaremodules that may be soldered onto a motherboard or otherwise integratedinto an electronic device), or they may be removable such as swappableflash memory modules (such as “thumb drives” or other removable mediadesigned for rapidly exchanging physical storage devices),“hot-swappable” hard disk drives or solid state drives, removableoptical storage discs, or other such removable media, and that suchintegral and removable storage media may be utilized interchangeably.Examples of program instructions include both object code, such as maybe produced by a compiler, machine code, such as may be produced by anassembler or a linker, byte code, such as may be generated by forexample a JAVA™ compiler and may be executed using a Java virtualmachine or equivalent, or files containing higher level code that may beexecuted by the computer using an interpreter (for example, scriptswritten in Python, Perl, Ruby, Groovy, or any other scripting language).

In some aspects, systems may be implemented on a standalone computingsystem. Referring now to FIG. 8, there is shown a block diagramdepicting a typical exemplary architecture of one or more aspects orcomponents thereof on a standalone computing system. Computing device 20includes processors 21 that may run software that carry out one or morefunctions or applications of aspects, such as for example a clientapplication 24. Processors 21 may carry out computing instructions undercontrol of an operating system 22 such as, for example, a version ofMICROSOFT WINDOWS™ operating system, APPLE macOS™ or iOS™ operatingsystems, some variety of the Linux operating system, ANDROID™ operatingsystem, or the like. In many cases, one or more shared services 23 maybe operable in system 20, and may be useful for providing commonservices to client applications 24. Services 23 may for example beWINDOWS™ services, user-space common services in a Linux environment, orany other type of common service architecture used with operating system21. Input devices 28 may be of any type suitable for receiving userinput, including for example a keyboard, touchscreen, microphone (forexample, for voice input), mouse, touchpad, trackball, or anycombination thereof. Output devices 27 may be of any type suitable forproviding output to one or more users, whether remote or local to system20, and may include for example one or more screens for visual output,speakers, printers, or any combination thereof. Memory 25 may berandom-access memory having any structure and architecture known in theart, for use by processors 21, for example to run software. Storagedevices 26 may be any magnetic, optical, mechanical, memristor, orelectrical storage device for storage of data in digital form (such asthose described above, referring to FIG. 7). Examples of storage devices26 include flash memory, magnetic hard drive, CD-ROM, and/or the like.

In some aspects, systems may be implemented on a distributed computingnetwork, such as one having any number of clients and/or servers.Referring now to FIG. 9, there is shown a block diagram depicting anexemplary architecture 30 for implementing at least a portion of asystem according to one aspect on a distributed computing network.According to the aspect, any number of clients 33 may be provided. Eachclient 33 may run software for implementing client-side portions of asystem; clients may comprise a system 20 such as that illustrated inFIG. 8. In addition, any number of servers 32 may be provided forhandling requests received from one or more clients 33. Clients 33 andservers 32 may communicate with one another via one or more electronicnetworks 31, which may be in various aspects any of the Internet, a widearea network, a mobile telephony network (such as CDMA or GSM cellularnetworks), a wireless network (such as WiFi, WiMAX, LTE, and so forth),or a local area network (or indeed any network topology known in theart; the aspect does not prefer any one network topology over anyother). Networks 31 may be implemented using any known networkprotocols, including for example wired and/or wireless protocols.

In addition, in some aspects, servers 32 may call external services 37when needed to obtain additional information, or to refer to additionaldata concerning a particular call. Communications with external services37 may take place, for example, via one or more networks 31. In variousaspects, external services 37 may comprise web-enabled services orfunctionality related to or installed on the hardware device itself. Forexample, in one aspect where client applications 24 are implemented on asmartphone or other electronic device, client applications 24 may obtaininformation stored in a server system 32 in the cloud or on an externalservice 37 deployed on one or more of a particular enterprise's oruser's premises.

In some aspects, clients 33 or servers 32 (or both) may make use of oneor more specialized services or appliances that may be deployed locallyor remotely across one or more networks 31. For example, one or moredatabases 34 may be used or referred to by one or more aspects. Itshould be understood by one having ordinary skill in the art thatdatabases 34 may be arranged in a wide variety of architectures andusing a wide variety of data access and manipulation means. For example,in various aspects one or more databases 34 may comprise a relationaldatabase system using a structured query language (SQL), while othersmay comprise an alternative data storage technology such as thosereferred to in the art as “NoSQL” (for example, HADOOP CASSANDRA™,GOOGLE BIGTABLE™, and so forth). In some aspects, variant databasearchitectures such as column-oriented databases, in-memory databases,clustered databases, distributed databases, or even flat file datarepositories may be used according to the aspect. It will be appreciatedby one having ordinary skill in the art that any combination of known orfuture database technologies may be used as appropriate, unless aspecific database technology or a specific arrangement of components isspecified for a particular aspect described herein. Moreover, it shouldbe appreciated that the term “database” as used herein may refer to aphysical database machine, a cluster of machines acting as a singledatabase system, or a logical database within an overall databasemanagement system. Unless a specific meaning is specified for a givenuse of the term “database”, it should be construed to mean any of thesesenses of the word, all of which are understood as a plain meaning ofthe term “database” by those having ordinary skill in the art.

Similarly, some aspects may make use of one or more security systems 36and configuration systems 35. Security and configuration management arecommon information technology (IT) and web functions, and some amount ofeach are generally associated with any IT or web systems. It should beunderstood by one having ordinary skill in the art that anyconfiguration or security subsystems known in the art now or in thefuture may be used in conjunction with aspects without limitation,unless a specific security 36 or configuration system 35 or approach isspecifically required by the description of any specific aspect.

FIG. 10 shows an exemplary overview of a computer system 40 as may beused in any of the various locations throughout the system. It isexemplary of any computer that may execute code to process data. Variousmodifications and changes may be made to computer system 40 withoutdeparting from the broader scope of the system and method disclosedherein. Central processor unit (CPU) 41 is connected to bus 42, to whichbus is also connected memory 43, nonvolatile memory 44, display 47,input/output (I/O) unit 48, and network interface card (NIC) 53. I/Ounit 48 may, typically, be connected to keyboard 49, pointing device 50,hard disk 52, and real-time clock 51. NIC 53 connects to network 54,which may be the Internet or a local network, which local network may ormay not have connections to the Internet. Also shown as part of system40 is power supply unit 45 connected, in this example, to a mainalternating current (AC) supply 46. Not shown are batteries that couldbe present, and many other devices and modifications that are well knownbut are not applicable to the specific novel functions of the currentsystem and method disclosed herein. It should be appreciated that someor all components illustrated may be combined, such as in variousintegrated applications, for example Qualcomm or Samsungsystem-on-a-chip (SOC) devices, or whenever it may be appropriate tocombine multiple capabilities or functions into a single hardware device(for instance, in mobile devices such as smartphones, video gameconsoles, in-vehicle computer systems such as navigation or multimediasystems in automobiles, or other integrated hardware devices).

In various aspects, functionality for implementing systems or methods ofvarious aspects may be distributed among any number of client and/orserver components. For example, various software modules may beimplemented for performing various functions in connection with thesystem of any particular aspect, and such modules may be variouslyimplemented to run on server and/or client components.

The skilled person will be aware of a range of possible modifications ofthe various aspects described above. Accordingly, the present inventionis defined by the claims and their equivalents.

What is claimed is:
 1. A system for testing of automated customerresponse systems at contact centers, comprising: a customer responsetesting system comprising a first plurality of programming instructionsstored in a memory of, and operating a processor of, a computing device,wherein the first plurality of programming instructions, when operatingon the processor, cause the computing device to: retrieve a test casefrom a test case database; retrieve a customer persona from a personadatabase; generate a simulated customer query based on the test case;create variations of the simulated customer query using a conversationmultiplier, each variation reflecting a likely real-world variant of thesimulated customer query; modify each query variation based on thecustomer persona, each modification reflecting one or more traits of thecustomer persona; connect to a customer response system at a contactcenter; transmit each modified query variation of the simulated customerquery to a customer response system at a contact center; receiveresponses to each modified query variation sent from the customerresponse system at the contact center; analyze each response received todetermine whether the response is appropriate to the modified queryvariation sent; and produce a result of the analysis.
 2. The system ofclaim 1, further comprising a real time conversation engine comprising asecond plurality of programming instructions stored in the memory of,and operating on the processor of, the computing device, wherein thesecond plurality of programming instructions, when operating on theprocessor, cause the computing device to: receive one or more of themodified query variations; analyze the one or more of the modified queryvariations to determine a context, dialect, or level of formality;receive a response corresponding to each of the one or more of themodified query variations; analyze each to determine a context, dialect,or level of formality; and compare the analysis of each of the one ormore of the modified query variations with the corresponding responsefor that modified query variation to determine an appropriateness of dieresponse.
 3. A method for testing of automated customer response systemsat contact centers, comprising the steps of: retrieving a test case froma test case database; retrieving a customer persona from a personadatabase; generating a simulated customer query based on the test caseas modified by the customer persona; creating variations of thesimulated customer query using a conversation multiplier, each variationreflecting a likely real-world variant of the simulated customer query;modifying each query variation based on the customer persona, eachmodification reflecting one or more traits of the customer persona;connecting to a customer response system at a contact center;transmitting each modified query variation of the simulated customerquery to a customer response system at a contact center; receivingresponses to each modified query variation sent from the customerresponse system at the contact center; analyzing each response receivedto determine whether the response is appropriate to the modified queryvariation sent; and producing a result of the analysis.
 4. The method ofclaim 3, further comprising the steps of: receiving one or more of themodified query variations; analyzing the one or more of the modifiedquery variations to determine a context, dialect, or level of formality;receiving a response corresponding to each of the one or more of themodified query variations; analyzing each to determine a context,dialect, or level of formality; and comparing the analysis of each ofthe one or more of the modified query variations with the correspondingresponse for that modified query variation to determine anappropriateness of the response.